System

Abstract

An object of a system according to an embodiment is to provide a quick and appropriate solution when a user faces a technical problem.SOLUTION: A system includes an input reception part, an analysis part, and a solution presentation part. The input receiving unit receives a question or a problem from a user. The analysis unit analyzes the question and the issue received by the input reception unit. The solution presentation unit provides an appropriate solution or procedure based on the result analyzed by the analysis unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technologies have had the problem that when a user encounters a technical problem, it is difficult to obtain a quick and appropriate solution.

[0005] The system according to the embodiment aims to provide a quick and appropriate solution when a user encounters a technical problem. [Means for solving the problem]

[0006] The system according to the embodiment includes an input receiving unit, an analysis unit, and a solution presenting unit. The input receiving unit receives questions and problems from users. The analysis unit analyzes the questions and problems received by the input receiving unit. The solution presenting unit provides an appropriate solution or procedure based on the results of the analysis by the analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide a quick and appropriate solution when a user encounters a technical problem. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The TechHelp ChatBot system according to an embodiment of the present invention is a system that provides real-time assistance for technical problems faced by users. With this system, users simply input their questions or issues in chat format, and the TechHelp ChatBot provides appropriate solutions and procedures to support problem resolution. This allows the TechHelp ChatBot system to quickly and accurately respond to various technical problems faced by users.

[0029] The TechHelp ChatBot system according to the embodiment includes an input receiving unit, an analysis unit, and a solution presenting unit. The input receiving unit receives user questions and issues. For example, a user can input a question such as, "My computer won't start. What should I do?" The input receiving unit also allows users to input questions and issues in chat format. For example, a user can input a question in text format. The analysis unit analyzes the questions and issues received by the input receiving unit. For example, a generation AI analyzes the content of the user's question and generates prompts to find an appropriate solution. The analysis unit also analyzes the content of the user's question, identifies the problem, and provides a solution. For example, the generation AI analyzes software error messages and presents possible causes and solutions. The solution presenting unit provides appropriate solutions and procedures based on the results of the analysis by the analysis unit. For example, the TechHelp ChatBot provides specific procedures to the user, such as, "If your computer won't start, first check that the power cable is connected properly. Then, try removing and reinserting the battery." The solution presenting unit also provides follow-up support after the user implements the proposed solution. For example, the TechHelp ChatBot system can respond to follow-up questions such as, "I tried the steps you presented, but the problem is still not resolved." This allows the TechHelp ChatBot system to quickly and accurately respond to users' technical problems. For example, the TechHelp ChatBot system can quickly and accurately respond to various technical problems that users face.

[0030] The analysis unit allows the generation AI to automatically search for related past questions and solutions based on the user's input and present them as reference information. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to search a database to see if similar questions have been asked in the past and present relevant solutions. For example, it may display past solutions such as "Please check the power cable connection." The analysis unit also allows the generation AI to search for past questions and solutions and present them to the user as reference information. For example, based on the user's past question history, the generation AI may provide information such as "When a similar problem occurred in the past, it was resolved by checking the power cable connection." This allows users to quickly resolve problems by referring to past questions and solutions.

[0031] The analysis unit allows the generation AI to analyze the user's input in real time and display an appropriate question format or a prompt for more detailed information. For example, when a user inputs "My computer won't start," the analysis unit allows the generation AI to display a specific question in real time, such as "Is the power cable connected?", prompting for more detailed information. The analysis unit also allows the generation AI to analyze the user's input in real time and display an appropriate question format or a prompt for more detailed information. For example, when a user inputs "Please tell me the meaning of the software error message," the generation AI displays a prompt such as "Please tell me specifically what the error message means." This improves the accuracy of problem-solving by prompting for an appropriate question format or more detailed information based on the user's input.

[0032] The input acceptance unit allows the user to use voice input, and the generation AI can convert it into text using voice recognition technology and perform analysis. For example, if the user speaks, "My computer won't start," the input acceptance unit converts it into text using voice recognition technology and presents an appropriate solution. The input acceptance unit also allows the user to use voice input, and the generation AI converts it into text using voice recognition technology and performs analysis. For example, if the user speaks, "Please tell me the meaning of the error message in this software," the generation AI converts it into text using voice recognition technology and analyzes the content of the error message. This improves user convenience by using voice input.

[0033] The input acceptance unit adds a function that allows users to attach images or screenshots when entering text, and the generation AI can analyze the visual information and provide a solution. For example, if a user enters "My computer won't start" and attaches a screenshot, the input acceptance unit uses image analysis technology to identify the cause of the problem and present a solution. The input acceptance unit also adds a function that allows users to attach images or screenshots when entering text, and the generation AI analyzes the visual information and provides a solution. For example, if a user enters "Please tell me the meaning of this software's error message" and attaches a screenshot of the error message, the generation AI uses image analysis technology to analyze the content of the error message. This allows for more accurate solutions to be provided by analyzing the visual information.

[0034] The analysis unit references the user's past question history and can quickly provide a solution if a similar problem recurs. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to reference the user's past question history and quickly provide a solution to similar problems. For example, it displays past solutions such as "Please check the power cable connection." The analysis unit also allows the generation AI to reference the user's past question history and quickly provide a solution if a similar problem recurs. For example, based on the past question history, the generation AI can provide information to the user such as "When a similar problem occurred in the past, it was resolved by checking the power cable connection." This makes it possible to quickly solve problems by referring to the past question history.

[0035] When analyzing a problem, the analysis unit can automatically search technical documents or manuals and extract the optimal solution. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to automatically search related technical documents and manuals and extract the optimal solution. For example, the generation AI may provide a solution such as "Please check the power cable connection." In addition, when analyzing a problem, the analysis unit can automatically search related technical documents and manuals and extract the optimal solution. For example, based on technical documents and manuals, the generation AI may provide information such as "Checking the power cable connection" to the user. This allows the generation AI to automatically search related technical documents and manuals and extract the optimal solution.

[0036] The analysis unit enables the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users. For example, if a user inputs "My computer won't start" in a different language, the analysis unit allows the generation AI to automatically recognize the language and provide an appropriate solution. For example, it may provide a solution such as "Check the power cable connection" in English. The analysis unit also enables the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users. For example, the generation AI may use a multilingual translation engine to automatically translate the user's question and provide an appropriate solution. This allows the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users.

[0037] The analysis unit can automatically obtain the user's device information or system settings and provide a customized solution based on that information. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to automatically obtain the user's device information and system settings and provide a customized solution based on that information. For example, the generation AI might provide a solution such as, "Your device is Windows 10, so please check that the power cable is connected." The analysis unit also allows the generation AI to automatically obtain the user's device information and system settings and provide a customized solution based on that information. For example, the generation AI might provide information such as, "Your device is a MacBook Pro, so please check that the power adapter is connected" based on the user's device information. This allows the generation AI to provide a customized solution based on the user's device information and system settings.

[0038] When presenting a solution, the solution presentation unit can customize the steps with a level of detail that corresponds to the user's skill level. For example, if a user inputs "My computer won't start," the generation AI will take the user's skill level into consideration and provide detailed steps for beginners. For example, it might present steps such as "Please check the power cable connection. Then, try removing and reinserting the battery." Furthermore, when presenting a solution, the solution presentation unit customizes the steps with a level of detail that corresponds to the user's skill level. For example, the generation AI might provide simple steps such as "Please check the power cable connection" for advanced users. This makes the steps easier to understand by providing steps that correspond to the user's skill level.

[0039] The solution presentation unit can visually explain the solution steps using videos or animations to make it easier for users to understand. For example, if a user inputs "My computer won't start," the solution presentation unit will have the generation AI visually explain the solution steps using videos. For example, it may provide a method such as "showing in a video the steps to check the power cable connection." The solution presentation unit also allows the generation AI to visually explain the solution steps using videos or animations to make it easier for users to understand. For example, the generation AI may use animations to visually explain "the steps to remove and reinsert the battery." This makes it easier for users to understand by providing a visual explanation using videos or animations.

[0040] The solution presentation unit can provide solution steps in multiple formats, allowing the user to select according to their preference. For example, if a user inputs "My computer won't start," the solution presentation unit can have the generation AI provide solution steps in text, audio, or video, allowing the user to select according to their preference. For example, the solution presentation unit can provide a method such as "Providing steps to check the power cable connection in text, audio, or video." The solution presentation unit can also have the generation AI provide solution steps in multiple formats, allowing the user to select according to their preference. For example, the generation AI can provide "Steps to check the power cable connection" in text format, and simultaneously provide it in audio or video format. This makes it possible to provide solutions in multiple formats, allowing support to be tailored to the user's preferences.

[0041] The solution presentation unit generates an automatic script to apply the solution steps directly to the user's device, minimizing manual operations. For example, if a user inputs "My computer won't start," the solution presentation unit has the generation AI generate the solution steps as an automatic script and apply it directly to the user's device. For example, it provides a method such as "automatically generating and executing a script to check the power cable connection." The solution presentation unit also generates an automatic script to apply the solution steps directly to the user's device, minimizing manual operations. For example, the generation AI uses a shell script to automate the "steps to remove and reinstall the battery" and apply it to the user's device. In this way, by generating an automatic script, manual operations can be minimized and the burden on the user can be reduced.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The TechHelp ChatBot system can further include a skill level determination unit that determines the user's skill level. The skill level determination unit analyzes the user's past question history and input content to determine the user's skill level. For example, if a user inputs "My computer won't start," the skill level determination unit determines that the user is a beginner based on the user's past question history and provides detailed instructions for beginners. Similarly, if the user inputs "Please tell me the meaning of this software error message," the skill level determination unit provides concise instructions for advanced users. This makes it possible to provide solutions customized to the user's skill level.

[0044] The TechHelp ChatBot system may further include a device information acquisition unit that automatically acquires the user's device information. The device information acquisition unit automatically acquires the user's device information and provides customized solutions based on that information. For example, if a user inputs "My computer won't start," the device information acquisition unit may detect that the user's device is Windows 10 and provide a solution tailored to Windows 10. Alternatively, if a user inputs "What does this software error message mean?" the device information acquisition unit may detect that the user's device is a MacBook Pro and provide a solution tailored to the MacBook Pro. This allows for more accurate solutions to be provided based on the user's device information.

[0045] The TechHelp ChatBot system can also be equipped with an image analysis unit that allows users to attach images or screenshots when typing, and the generation AI analyzes the visual information and provides solutions. For example, if a user types "My computer won't start" and attaches a screenshot, the generation AI uses image analysis technology to identify the cause of the problem and provide a solution. Similarly, if a user types "Please tell me the meaning of this software's error message" and attaches a screenshot of the error message, the generation AI uses image analysis technology to analyze the content of the error message. This allows for more accurate solutions to be provided by analyzing visual information.

[0046] The TechHelp ChatBot system can also include a speech recognition unit that allows users to input voice commands, with the generation AI converting the voice command into text using speech recognition technology and analyzing it. For example, if a user inputs "My computer won't start," the generation AI converts the voice command into text using speech recognition technology and presents an appropriate solution. Similarly, if a user inputs "Please tell me the meaning of this software's error message," the generation AI converts the voice command into text using speech recognition technology and analyzes the error message. This allows for improved user convenience through the use of speech input.

[0047] The TechHelp ChatBot system can also be equipped with a history reference section that references the user's past question history and quickly provides a solution if a similar problem recurs. For example, if a user types, "My computer won't start," the generation AI references the user's past question history and quickly provides a solution to the similar problem. For example, it may display a past solution such as, "Please check the power cable connection." The history reference section also allows the generation AI to reference the user's past question history and quickly provide a solution if a similar problem recurs. For example, the generation AI may provide the user with information such as, "When a similar problem occurred in the past, it was resolved by checking the power cable connection" based on the past question history. This allows for quick problem resolution by referring to the past question history.

[0048] The TechHelp ChatBot system can also be equipped with a document search unit that automatically searches technical documents or manuals when analyzing a problem and extracts the optimal solution. For example, if a user enters "My computer won't start," the document search unit automatically searches related technical documents and manuals to extract the optimal solution. For example, it may present a solution such as "Please check the power cable connection." The document search unit also automatically searches related technical documents and manuals when analyzing a problem and extracts the optimal solution. For example, the generation AI may provide the user with information such as "Checking the power cable connection" based on technical documents and manuals. This allows the optimal solution to be provided by automatically searching related technical documents and manuals.

[0049] The processing flow of the first embodiment will be briefly explained below.

[0050] Step 1: The input accepting unit accepts questions and problems from users. For example, a user can enter a question such as, "My computer won't start. What should I do?" The input accepting unit also allows users to enter questions and problems in chat format. For example, a user can enter a question in text format. Step 2: The analysis unit analyzes the questions and issues received by the input reception unit. For example, the generation AI analyzes the content of the user's question and generates a prompt to find an appropriate solution. The analysis unit also analyzes the content of the user's question, identifies the problem, and provides a solution. For example, the generation AI analyzes software error messages and presents possible causes and solutions. Step 3: The solution suggestion unit provides appropriate solutions and procedures based on the results of the analysis by the analysis unit. For example, TechHelp ChatBot provides specific procedures to the user, such as, "If your computer won't start, first check that the power cable is connected properly. Then, try removing and reinserting the battery." The solution suggestion unit also follows up after the user implements the proposed solution. For example, it responds to follow-up questions from the user, such as, "I tried the proposed steps, but the problem still persists."

[0051] (Example 2) The TechHelp ChatBot system according to an embodiment of the present invention is a system that provides real-time assistance for technical problems faced by users. With this system, users simply input their questions or issues in chat format, and the TechHelp ChatBot provides appropriate solutions and procedures to support problem resolution. This allows the TechHelp ChatBot system to quickly and accurately respond to various technical problems faced by users.

[0052] The TechHelp ChatBot system according to the embodiment includes an input receiving unit, an analysis unit, and a solution presenting unit. The input receiving unit receives user questions and issues. For example, a user can input a question such as, "My computer won't start. What should I do?" The input receiving unit also allows users to input questions and issues in chat format. For example, a user can input a question in text format. The analysis unit analyzes the questions and issues received by the input receiving unit. For example, a generation AI analyzes the content of the user's question and generates prompts to find an appropriate solution. The analysis unit also analyzes the content of the user's question, identifies the problem, and provides a solution. For example, the generation AI analyzes software error messages and presents possible causes and solutions. The solution presenting unit provides appropriate solutions and procedures based on the results of the analysis by the analysis unit. For example, the TechHelp ChatBot provides specific procedures to the user, such as, "If your computer won't start, first check that the power cable is connected properly. Then, try removing and reinserting the battery." The solution presenting unit also provides follow-up support after the user implements the proposed solution. For example, the TechHelp ChatBot system can respond to follow-up questions such as, "I tried the steps you presented, but the problem is still not resolved." This allows the TechHelp ChatBot system to quickly and accurately respond to users' technical problems. For example, the TechHelp ChatBot system can quickly and accurately respond to various technical problems that users face.

[0053] The analysis unit allows the generation AI to automatically search for related past questions and solutions based on the user's input and present them as reference information. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to search a database to see if similar questions have been asked in the past and present relevant solutions. For example, it may display past solutions such as "Please check the power cable connection." The analysis unit also allows the generation AI to search for past questions and solutions and present them to the user as reference information. For example, based on the user's past question history, the generation AI may provide information such as "When a similar problem occurred in the past, it was resolved by checking the power cable connection." This allows users to quickly resolve problems by referring to past questions and solutions.

[0054] The analysis unit allows the generation AI to analyze the user's input in real time and display an appropriate question format or a prompt for more detailed information. For example, when a user inputs "My computer won't start," the analysis unit allows the generation AI to display a specific question in real time, such as "Is the power cable connected?", prompting for more detailed information. The analysis unit also allows the generation AI to analyze the user's input in real time and display an appropriate question format or a prompt for more detailed information. For example, when a user inputs "Please tell me the meaning of the software error message," the generation AI displays a prompt such as "Please tell me specifically what the error message means." This improves the accuracy of problem-solving by prompting for an appropriate question format or more detailed information based on the user's input.

[0055] The analysis unit can use the emotion estimation function to analyze the user's emotion when typing and automatically generate a support message to reduce stress and anxiety. For example, when a user types "My computer won't start," the emotion estimation function detects the user's stress and displays a support message such as "Don't worry, we'll find a solution right away." The analysis unit also uses the emotion estimation function to analyze the user's emotion when typing and automatically generate a support message to reduce stress and anxiety. For example, if the emotion estimation function detects the user's anxiety, it displays a message such as "Don't worry, we'll do our best to help you solve the problem." In this way, by providing a support message that matches the user's emotion, stress and anxiety can be reduced.

[0056] The input acceptance unit allows the user to use voice input, and the generation AI can convert it into text using voice recognition technology and perform analysis. For example, if the user speaks, "My computer won't start," the input acceptance unit converts it into text using voice recognition technology and presents an appropriate solution. The input acceptance unit also allows the user to use voice input, and the generation AI converts it into text using voice recognition technology and performs analysis. For example, if the user speaks, "Please tell me the meaning of the error message in this software," the generation AI converts it into text using voice recognition technology and analyzes the content of the error message. This improves user convenience by using voice input.

[0057] The input acceptance unit adds a function that allows users to attach images or screenshots when entering text, and the generation AI can analyze the visual information and provide a solution. For example, if a user enters "My computer won't start" and attaches a screenshot, the input acceptance unit uses image analysis technology to identify the cause of the problem and present a solution. The input acceptance unit also adds a function that allows users to attach images or screenshots when entering text, and the generation AI analyzes the visual information and provides a solution. For example, if a user enters "Please tell me the meaning of this software's error message" and attaches a screenshot of the error message, the generation AI uses image analysis technology to analyze the content of the error message. This allows for more accurate solutions to be provided by analyzing the visual information.

[0058] The analysis unit uses the emotion estimation function to analyze the emotion of the user when typing in real time and provide positive feedback, thereby improving user satisfaction. For example, when the user types "My computer won't start," the emotion estimation function detects the user's stress and provides positive feedback such as "Don't worry, we'll find a solution right away." The analysis unit also uses the emotion estimation function to analyze the emotion of the user when typing in real time and provide positive feedback. For example, if the emotion estimation function detects the user's anxiety, it displays a message such as "Don't worry, we'll do our best to support you in resolving the problem." By providing positive feedback in this way, user satisfaction is improved.

[0059] The analysis unit references the user's past question history and can quickly provide a solution if a similar problem recurs. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to reference the user's past question history and quickly provide a solution to similar problems. For example, it displays past solutions such as "Please check the power cable connection." The analysis unit also allows the generation AI to reference the user's past question history and quickly provide a solution if a similar problem recurs. For example, based on the past question history, the generation AI can provide information to the user such as "When a similar problem occurred in the past, it was resolved by checking the power cable connection." This makes it possible to quickly solve problems by referring to the past question history.

[0060] When analyzing a problem, the analysis unit can automatically search technical documents or manuals and extract the optimal solution. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to automatically search related technical documents and manuals and extract the optimal solution. For example, the generation AI may provide a solution such as "Please check the power cable connection." In addition, when analyzing a problem, the analysis unit can automatically search related technical documents and manuals and extract the optimal solution. For example, based on technical documents and manuals, the generation AI may provide information such as "Checking the power cable connection" to the user. This allows the generation AI to automatically search related technical documents and manuals and extract the optimal solution.

[0061] The analysis unit can use the emotion estimation function to set priorities for reducing stress based on the user's emotional state and provide solutions. For example, when the user inputs "My computer won't start," the emotion estimation function detects the user's stress, sets priorities for reducing stress, and provides solutions. For example, simple steps such as "Please check that the power cable is connected" are presented. The analysis unit also uses the emotion estimation function to set priorities for reducing stress and provide solutions, taking the user's emotional state into consideration. For example, if the emotion estimation function detects the user's anxiety, it will present simple steps such as "First, please check that the power cable is connected." In this way, stress can be reduced and effective solutions can be provided by taking the user's emotional state into consideration.

[0062] The analysis unit enables the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users. For example, if a user inputs "My computer won't start" in a different language, the analysis unit allows the generation AI to automatically recognize the language and provide an appropriate solution. For example, it may provide a solution such as "Check the power cable connection" in English. The analysis unit also enables the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users. For example, the generation AI may use a multilingual translation engine to automatically translate the user's question and provide an appropriate solution. This allows the generation AI to respond to questions in different languages ​​and provide appropriate solutions to global users.

[0063] The analysis unit can automatically obtain the user's device information or system settings and provide a customized solution based on that information. For example, if a user inputs "My computer won't start," the analysis unit allows the generation AI to automatically obtain the user's device information and system settings and provide a customized solution based on that information. For example, the generation AI might provide a solution such as, "Your device is Windows 10, so please check that the power cable is connected." The analysis unit also allows the generation AI to automatically obtain the user's device information and system settings and provide a customized solution based on that information. For example, the generation AI might provide information such as, "Your device is a MacBook Pro, so please check that the power adapter is connected" based on the user's device information. This allows the generation AI to provide a customized solution based on the user's device information and system settings.

[0064] The analysis unit can use the emotion estimation function to adjust the order in which solutions are presented according to the user's emotions, thereby improving user satisfaction. For example, when a user inputs "My computer won't start," the emotion estimation function detects the user's stress and provides solutions by setting priorities for reducing stress. For example, solutions are presented starting with simple steps such as "First, check that the power cable is connected." The analysis unit also uses the emotion estimation function to adjust the order in which solutions are presented according to the user's emotions. For example, if the emotion estimation function detects the user's anxiety, solutions are presented starting with simple steps such as "First, check that the power cable is connected." In this way, satisfaction is improved by adjusting the order in which solutions are presented according to the user's emotions.

[0065] When presenting a solution, the solution presentation unit can customize the steps with a level of detail that corresponds to the user's skill level. For example, if a user inputs "My computer won't start," the generation AI will take the user's skill level into consideration and provide detailed steps for beginners. For example, it might present steps such as "Please check the power cable connection. Then, try removing and reinserting the battery." Furthermore, when presenting a solution, the solution presentation unit customizes the steps with a level of detail that corresponds to the user's skill level. For example, the generation AI might provide simple steps such as "Please check the power cable connection" for advanced users. This makes the steps easier to understand by providing steps that correspond to the user's skill level.

[0066] The solution presentation unit can visually explain the solution steps using videos or animations to make it easier for users to understand. For example, if a user inputs "My computer won't start," the solution presentation unit will have the generation AI visually explain the solution steps using videos. For example, it may provide a method such as "showing in a video the steps to check the power cable connection." The solution presentation unit also allows the generation AI to visually explain the solution steps using videos or animations to make it easier for users to understand. For example, the generation AI may use animations to visually explain "the steps to remove and reinsert the battery." This makes it easier for users to understand by providing a visual explanation using videos or animations.

[0067] The solution presentation unit can use the emotion estimation function to incorporate encouraging or reassuring messages into the procedure instructions, taking into account the user's emotional state. For example, when the user inputs "My computer won't start," the emotion estimation function detects the user's stress and incorporates encouraging or reassuring messages into the procedure instructions. For example, a message such as "Don't worry, we'll find a solution right away" is displayed. The solution presentation unit also uses the emotion estimation function to incorporate encouraging or reassuring messages into the procedure instructions, taking into account the user's emotional state. For example, if the emotion estimation function detects the user's anxiety, a message such as "Don't worry, we'll do our best to support you in resolving the problem." This improves user satisfaction by providing encouraging or reassuring messages that take into account the user's emotional state.

[0068] The solution presentation unit can provide solution steps in multiple formats, allowing the user to select according to their preference. For example, if a user inputs "My computer won't start," the solution presentation unit can have the generation AI provide solution steps in text, audio, or video, allowing the user to select according to their preference. For example, the solution presentation unit can provide a method such as "Providing steps to check the power cable connection in text, audio, or video." The solution presentation unit can also have the generation AI provide solution steps in multiple formats, allowing the user to select according to their preference. For example, the generation AI can provide "Steps to check the power cable connection" in text format, and simultaneously provide it in audio or video format. This makes it possible to provide solutions in multiple formats, allowing support to be tailored to the user's preferences.

[0069] The solution presentation unit generates an automatic script to apply the solution steps directly to the user's device, minimizing manual operations. For example, if a user inputs "My computer won't start," the solution presentation unit has the generation AI generate the solution steps as an automatic script and apply it directly to the user's device. For example, it provides a method such as "automatically generating and executing a script to check the power cable connection." The solution presentation unit also generates an automatic script to apply the solution steps directly to the user's device, minimizing manual operations. For example, the generation AI uses a shell script to automate the "steps to remove and reinstall the battery" and apply it to the user's device. In this way, by generating an automatic script, manual operations can be minimized and the burden on the user can be reduced.

[0070] The solution presentation unit can use the emotion estimation function to monitor the user's emotional reactions in real time when the user executes a solution and provide additional support as needed. For example, when the user inputs "My computer won't start" and executes a solution, the emotion estimation function monitors the user's emotional reactions in real time and provides additional support as needed. For example, a method is provided in which "if stress is detected while executing a procedure to check the power cable connection, an additional support message is displayed." The solution presentation unit also uses the emotion estimation function to monitor the user's emotional reactions in real time when the user executes a solution and provides additional support as needed. For example, if the emotion estimation function detects the user's anxiety, a message such as "Don't worry, we will do our best to support you in resolving the problem." In this way, by monitoring the user's emotional reactions in real time and providing additional support as needed, user satisfaction is improved.

[0071] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0072] The TechHelp ChatBot system can further include a skill level determination unit that determines the user's skill level. The skill level determination unit analyzes the user's past question history and input content to determine the user's skill level. For example, if a user inputs "My computer won't start," the skill level determination unit determines that the user is a beginner based on the user's past question history and provides detailed instructions for beginners. Similarly, if the user inputs "Please tell me the meaning of this software error message," the skill level determination unit provides concise instructions for advanced users. This makes it possible to provide solutions customized to the user's skill level.

[0073] The TechHelp ChatBot system may further include a device information acquisition unit that automatically acquires the user's device information. The device information acquisition unit automatically acquires the user's device information and provides customized solutions based on that information. For example, if a user inputs "My computer won't start," the device information acquisition unit may detect that the user's device is Windows 10 and provide a solution tailored to Windows 10. Alternatively, if a user inputs "What does this software error message mean?" the device information acquisition unit may detect that the user's device is a MacBook Pro and provide a solution tailored to the MacBook Pro. This allows for more accurate solutions to be provided based on the user's device information.

[0074] The TechHelp ChatBot system can also include an emotion order adjustment unit that estimates the user's emotions and adjusts the order in which solutions are presented based on the estimated user emotions. When a user enters "My computer won't start," the emotion order adjustment unit detects the user's stress and provides solutions by prioritizing them to reduce stress. For example, it might start with simple steps such as "First, check that the power cable is connected." If the emotion order adjustment unit detects the user's anxiety, it will display a message such as "Don't worry, we will do our best to support you in resolving the problem." This allows the system to adjust the order in which solutions are presented based on the user's emotional state, thereby improving user satisfaction.

[0075] The TechHelp ChatBot system can also include an emotion message module that estimates the user's emotions and incorporates encouraging and reassuring messages into the procedure instructions based on the estimated user emotions. When a user types "My computer won't start," the emotion message module detects the user's stress and displays a message such as "Don't worry, we'll find a solution right away." If the emotion message module detects the user's anxiety, it displays a message such as "Don't worry, we'll do our best to support you in resolving the problem." This allows the system to improve user satisfaction by providing encouraging and reassuring messages that take the user's emotional state into consideration.

[0076] The TechHelp ChatBot system can further include an emotion prioritization unit that estimates the user's emotions and provides solutions by prioritizing stress reduction based on the estimated user emotions. When a user inputs "My computer won't start," the emotion prioritization unit detects the user's stress, sets priorities for stress reduction, and provides solutions. For example, it may suggest simple steps such as "First, check that the power cable is connected." If the emotion prioritization unit detects the user's anxiety, it will display a message such as "Don't worry, we will do our best to support you in resolving the problem." This allows the system to reduce stress and provide effective solutions by taking the user's emotional state into consideration.

[0077] The TechHelp ChatBot system can further include an emotion feedback unit that estimates the user's emotions and provides positive feedback based on the estimated user emotions. When a user types "My computer won't start," the emotion feedback unit detects the user's stress and provides positive feedback such as "Don't worry, we'll find a solution right away." If the emotion feedback unit detects the user's anxiety, it displays a message such as "Don't worry, we'll do our best to help you solve the problem." This positive feedback can improve user satisfaction.

[0078] The TechHelp ChatBot system can also be equipped with an image analysis unit that allows users to attach images or screenshots when typing, and the generation AI analyzes the visual information and provides solutions. For example, if a user types "My computer won't start" and attaches a screenshot, the generation AI uses image analysis technology to identify the cause of the problem and provide a solution. Similarly, if a user types "Please tell me the meaning of this software's error message" and attaches a screenshot of the error message, the generation AI uses image analysis technology to analyze the content of the error message. This allows for more accurate solutions to be provided by analyzing visual information.

[0079] The TechHelp ChatBot system can also include a speech recognition unit that allows users to input voice commands, with the generation AI converting the voice command into text using speech recognition technology and analyzing it. For example, if a user inputs "My computer won't start," the generation AI converts the voice command into text using speech recognition technology and presents an appropriate solution. Similarly, if a user inputs "Please tell me the meaning of this software's error message," the generation AI converts the voice command into text using speech recognition technology and analyzes the error message. This allows for improved user convenience through the use of speech input.

[0080] The TechHelp ChatBot system can also be equipped with a history reference section that references the user's past question history and quickly provides a solution if a similar problem recurs. For example, if a user types, "My computer won't start," the generation AI references the user's past question history and quickly provides a solution to the similar problem. For example, it may display a past solution such as, "Please check the power cable connection." The history reference section also allows the generation AI to reference the user's past question history and quickly provide a solution if a similar problem recurs. For example, the generation AI may provide the user with information such as, "When a similar problem occurred in the past, it was resolved by checking the power cable connection" based on the past question history. This allows for quick problem resolution by referring to the past question history.

[0081] The TechHelp ChatBot system can also be equipped with a document search unit that automatically searches technical documents or manuals when analyzing a problem and extracts the optimal solution. For example, if a user enters "My computer won't start," the document search unit automatically searches related technical documents and manuals to extract the optimal solution. For example, it may present a solution such as "Please check the power cable connection." The document search unit also automatically searches related technical documents and manuals when analyzing a problem and extracts the optimal solution. For example, the generation AI may provide the user with information such as "Checking the power cable connection" based on technical documents and manuals. This allows the optimal solution to be provided by automatically searching related technical documents and manuals.

[0082] The processing flow of the second embodiment will be briefly explained below.

[0083] Step 1: The input accepting unit accepts questions and problems from users. For example, a user can enter a question such as, "My computer won't start. What should I do?" The input accepting unit also allows users to enter questions and problems in chat format. For example, a user can enter a question in text format. Step 2: The analysis unit analyzes the questions and issues received by the input reception unit. For example, the generation AI analyzes the content of the user's question and generates a prompt to find an appropriate solution. The analysis unit also analyzes the content of the user's question, identifies the problem, and provides a solution. For example, the generation AI analyzes software error messages and presents possible causes and solutions. Step 3: The solution suggestion unit provides appropriate solutions and procedures based on the results of the analysis by the analysis unit. For example, TechHelp ChatBot provides specific procedures to the user, such as, "If your computer won't start, first check that the power cable is connected properly. Then, try removing and reinserting the battery." The solution suggestion unit also follows up after the user implements the proposed solution. For example, it responds to follow-up questions from the user, such as, "I tried the proposed steps, but the problem still persists."

[0084] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0085] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0086] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0087] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0088] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0089] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0090] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0091] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0092] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0093] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0094] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0095] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0096] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0097] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0098] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0099] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0100] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0101] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0102] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0103] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0104] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0105] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0106] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0107] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0108] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0109] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0110] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0111] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0112] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0113] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0114] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0115] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0116] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0117] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0118] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0119] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0120] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0121] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0122] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0123] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0124] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0125] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0126] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0127] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0128] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0129] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0130] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0131] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0132] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0133] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0134] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0135] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0136] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0137] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0138] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0139] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0140] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0141] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0142] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0143] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0144] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0145] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0146] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0147] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0148] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0149] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0150] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0151] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an input receiving unit that receives questions and assignments from users; an analysis unit that analyzes the questions and tasks accepted by the input acceptance unit; a solution presentation unit that provides an appropriate solution or procedure based on the results of the analysis by the analysis unit. A system characterized by:

2. The analysis unit Based on the user's input, the generation AI automatically searches for related past questions or solutions and presents them as reference information.

2. The system of claim 1.

3. The input receiving unit Allows users to use voice input, and the generation AI converts it into text using voice recognition technology to perform the analysis.

2. The system of claim 1.

4. The analysis unit By referring to the user's past question history, if a similar problem occurs again, the solution is quickly provided.

2. The system of claim 1.

5. The solution presentation unit When presenting the solution, the procedure is customized with a level of detail appropriate to the user's technical level.

2. The system of claim 1.

6. The analysis unit Analyzing the user's emotions when they input information and automatically generating support messages to reduce stress or anxiety 2. The system of claim 1.

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